• magnetic resonance linear accelerator
• measurement method
• mechanical accuracy

• 2023-I2M-C&T-B-076 CAMS Innovation Fund for Medical Sciences
• 2023-I2M-C&T-B-095 CAMS Innovation Fund for Medical Sciences
• 2024-RW320-05 Non-profit Central Research Institute Fund of Chinese Academy of Medical Sciences
• 2022-CICAMS-80102022203 National High Level Hospital Clinical Research Funding

We developed a quality assurance (QA) method to determine the isocenter congruence of Optical Surface Monitoring System (OSMS, Varian, CA, USA), kilovoltage (kV), and megavoltage (MV) imaging, and the radiation isocenter using a single setup of the OSMS phantom for frameless Stereotactic Radiosurgery (SRS) treatment. After aligning the phantom to the OSMS isocenter, a cone‐beam computed tomography (CBCT) of the phantom was acquired and registered to a computed tomography (CT) scan of the phantom to determine the CBCT isocenter. Without moving the phantom, MV and kV images were simultaneously acquired at four gantry angles to localize MV and kV isocenters. Then, Winston‐Lutz (W‐L) test images of the central BB in the phantom were acquired to analyze the radiation isocenter. The gantry and couch were automatically controlled using the TrueBeam Developer Mode during MV, kV, and W‐L image acquisition. All the images were acquired weekly for 17 weeks to track the congruence of all the imaging modalities' isocenter in six‐dimensional (6D) translations and rotations, and the radiation isocenter in three‐dimensional (3D) translations. The shifts of isocenters of all imaging modalities and the radiation isocenter from the OSMS isocenter were within 0.2 mm and 0.2° on average over 17 weeks. The maximum discrepancy between OSMS and other imaging modalities or radiation isocenters was 0.8 mm and 0.3°. However, systematic shifts of radiation isocenter anteriorly and laterally relative to the OSMS isocenter were observed. The measured discrepancies were consistent from week‐to‐week except for two weeks when the isocenter discrepancies of 0.8 mm were noted due to drifts of the OSMS isocenter. Once recalibration was performed on OSMS, the discrepancy was reduced to 0.3 mm and 0.2°.By performing the proposed QA on a weekly basis, the isocenter congruencies of multiple imaging systems and radiation isocenter were validated for a linear accelerator.

• automation
• imaging quality assurance
• optical imaging

Lung cancer is one of the most common malignant tumors. It has the highest incidence and mortality rate of all cancers worldwide. Late diagnosis of non-small cell lung cancer (NSCLC) is very common in clinical practice, and most patients miss the chance for radical surgery. Thus, radiotherapy plays an indispensable role in the treatment of NSCLC. Radiotherapy technology has evolved from the classic two-dimensional approach to three-dimensional conformal and intensity-modulated radiotherapy. However, how to ensure delivery of an accurate dose to the tumor while minimizing the irradiation of normal tissues remains a huge challenge for radiation oncologists, especially due to the positioning error between fractions and the autonomous movement of organs. In recent years, image-guided radiotherapy (IGRT) has greatly increased the accuracy of tumor irradiation while reducing the irradiation dose delivered to healthy tissues and organs. This paper presents a brief review of the definition of IGRT and the various technologies and applications of IGRT. IGRT can help ensure accurate dosing of the target area and reduce radiation damage to the surrounding normal tissue. IGRT may increase the local control rate of tumors and reduce the incidence of radio-therapeutic complications.

• Non-small cell lung cancer
• Radiotherapy
• Image-guided radiotherapy
• Intensity-modulated radiotherapy
• Positioning error

• geometric calibration
• isocenter check
• linear accelerator
• radiation therapy

The poor quality of megavoltage (MV) images from electronic portal imaging device (EPID) hinders visual verification of tumor targeting accuracy particularly during markerless tumor tracking. The aim of this study was to investigate the effect of a few representative image processing treatments on visual verification and detection capability of tumors under auto tracking.

Images of QC‐3 quality phantom, a single patient's setup image, and cine images of two‐lung cancer patients were acquired. Three image processing methods were individually employed to the same original images. For each deblurring, contrast enhancement, and denoising, a total variation deconvolution, contrast‐limited adaptive histogram equalization (CLAHE), and median filter were adopted, respectively. To study the effect of image enhancement on tumor auto‐detection, a tumor tracking algorithm was adopted in which the tumor position was determined as the minimum point of the mean of the sum of squared pixel differences (MSSD) between two images. The detectability and accuracy were compared.

Deblurring of a quality phantom image yielded sharper edges, while the contrast‐enhanced image was more readable with improved structural differentiation. Meanwhile, the denoising operation resulted in noise reduction, however, at the cost of sharpness. Based on comparison of pixel value profiles, contrast enhancement outperformed others in image perception. During the tracking experiment, only contrast enhancement resulted in tumor detection in all images using our tracking algorithm. Deblurring failed to determine the target position in two frames out of a total of 75 images. For original and denoised set, target location was not determined for the same five images. Meanwhile, deblurred image showed increased detection accuracy compared with the original set. The denoised image resulted in decreased accuracy. In the case of contrast‐improved set, the tracking accuracy was nearly maintained as that of the original image.

Considering the effect of each processing on tumor tracking and the visual perception in a limited time, contrast enhancement would be the first consideration to visually verify the tracking accuracy of tumors on MV EPID without sacrificing tumor detectability and detection accuracy.

• contrast enhancement
• deblurring
• denoising
• image quality
• megavoltage electronic portal imaging device
• tumor tracking

• adaptive
• image-guided
• radiotherapy/radiation therapy

• Combined Modality Therapy
• Humans
• Neoplasms/radiotherapy
• Radiotherapy, Image-Guided/methods
• Radiotherapy, Image-Guided/standards

Stereotactic radiosurgery (SRS) places great demands on spatial accuracy. Steel BBs used as markers in quality assurance (QA) phantoms are clearly visible in MV and planar kV images, but artifacts compromise cone‐beam CT (CBCT) isocenter localization. The purpose of this work was to develop a QA phantom for measuring with sub‐mm accuracy isocenter congruence of planar kV, MV, and CBCT imaging systems and to design a practical QA procedure that includes daily Winston‐Lutz (WL) tests and does not require computer aid. The salient feature of the phantom (Universal Alignment Ball (UAB)) is a novel marker for precisely localizing isocenters of CBCT, planar kV, and MV beams. It consists of a 25.4 mm diameter sphere of polymethylmetacrylate (PMMA) containing a concentric 6.35 mm diameter tungsten carbide ball. The large density difference between PMMA and the polystyrene foam in which the PMMA sphere is embedded yields a sharp image of the sphere for accurate CBCT registration. The tungsten carbide ball serves in finding isocenter in planar kV and MV images and in doing WL tests. With the aid of the UAB, CBCT isocenter was located within 0.10±0.05 mm of its true positon, and MV isocenter was pinpointed in planar images to within 0.06±0.04 mm. In clinical morning QA tests extending over an 18 months period the UAB consistently yielded measurements with sub‐mm accuracy. The average distance between isocenter defined by orthogonal kV images and CBCT measured 0.16±0.12 mm. In WL tests the central ray of anterior beams defined by a 1.5×1.5 cm2 MLC field agreed with CBCT isocenter within 0.03±0.14 mm in the lateral direction and within 0.10±0.19 mm in the longitudinal direction. Lateral MV beams approached CBCT isocenter within 0.00±0.11 mm in the vertical direction and within ‐0.14±0.15 mm longitudinally. It took therapists about 10 min to do the tests. The novel QA phantom allows pinpointing CBCT and MV isocenter positions to better than 0.2 mm, using visual image registration. Under CBCT guidance, MLC‐defined beams are deliverable with sub‐mm spatial accuracy. The QA procedure is practical for daily tests by therapists.

PACS number(s): 87.53.Ly, 87.56.Fc

Geometric or mechanical accuracy of kV and MV imaging systems of two Varian TrueBeam linacs have been monitored by two geomertirc calibration systems, Varian IsoCal geometric calibration system and home‐developed gQA system. Results of both systems are cross‐checked and the long‐term geometric stabilities of linacs are evaluated. Two geometric calibration methodologies have been used to assess kV and MV imaging systems and their coincidence periodically on two TrueBeam linacs for about one year. Both systems analyze kV or MV projection images of special designed phantoms to retrieve geometric parameters of the imaging systems. The isocenters — laser isocenter and centers of rotations of kV imager and EPID — are then calculated, based on results of multiple projections from different angles. Long‐term calibration results from both systems are compared for cross‐checking. There are 24 sessions of side‐by‐side calibrations performed by both systems on two TrueBeam linacs. All the disagreements of isocenters between two calibrations systems are less than 1 mm with ± 0.1 mm SD. Most of the large disagreements occurred in vertical direction (AP direction), with an averaged disagreement of 0.45 mm. The average disagreements of isocenters are 0.09 mm in other directions. Additional to long‐term calibration monitoring, for the accuracy test, special tests were performed by misaligning QA phantoms on purpose (5 mm away from setup isocenter in AP, SI, and lateral directions) to test the liability performance of both systems with the known deviations. The errors are within 0.5 mm. Both geometric calibration systems, IsoCal and gQA, are capable of detecting geometric deviations of kV and MV imaging systems of linacs. The long‐term evaluation also shows that the deviations of geometric parameters and the geometric accuracies of both linacs are small and very consistent during the one‐year study period.

PACS number: 87.56.Fc

The goal of this work was to develop and evaluate an end‐to‐end test for determining and verifying image‐guided radiation therapy setup accuracy relative to the radiation isocenter. This was done by placing a cube phantom with a central tungsten sphere directly on the treatment table and offset from isocenter either by 5.0 mm in the longitudinal, lateral, and vertical dimensions or by a random amount. A high‐resolution cone‐beam CT image was acquired and aligned with the tungsten sphere in the reference CT image. The table was shifted per this alignment, and megavoltage anterior–posterior and lateral images were acquired with the electronic portal imaging device. Agreement between the radiation isocenter (based on the MV field) and the center of the sphere (i.e., the alignment point based on kV imaging) was determined for each image via Winston‐Lutz analysis. This procedure was repeated 10 times to determine short‐term reproducibility, and then repeated daily for 51 days in a clinical setting. The short‐term reproducibility test yielded a mean 3D vector displacement of 0.9±0.15mm between the imaging‐based isocenter and the radiation isocenter, with a maximum displacement of 1.1 mm. The clinical reproducibility test yielded a mean displacement of 1.1±0.4mm with a maximum of 2.0 mm when the cube was offset by 5.0 mm, and a mean displacement of 0.9±0.3mm with a maximum of 1.8 mm when the cube was offset by a random amount. These differences were observed in all directions and were independent of the magnitude of the couch shift. This test was quick and easy to implement clinically and highlighted setup inaccuracies in an image‐guided radiation therapy environment.

PACS numbers: 87.55.km; 87.55.Qr; 87.56.Fc